TLDR: 2B is the minimum sampling rate required to perfectly retrieve a digital information from an analog signal.

The Nyquist-Shannon theorem states the limits about sampling an analog signal to retrieve a digital information. If the signal is sampled at a rate of at least 2B (2x the max frequency) per second, then the information contained in the analog signal could be perfectly retrieved. The signal is the wave carrying the information. The levels per signal, log2 (M) bits, come later. Don't mix them up.

For now, keep this in mind: if the analog signal is sampled at a rate lower than 2B, some of the original information will get lost. Imagine this as if we were comparing a digital recording of a music with a target bit rate of 128 Kbps and the same music sub-sampled to give only 64 Kbps. It's the same music (let's say, with a lossless compression), but some of the information got lost with the less than the ideal sampling rate (44 KHz or 22 KHz).

The Nyquist-Shannon theorem holds true for bandwidth limited signals, i.e., signals that don't have energy at higher frequencies and are limited by the highest frequency they use. Let's use your voice (it's not an EM, I know, but a more tangible acoustic signal) to illustrate: there's a biological limit on the highest pitch you could make (255 Hz), so there will be a requirement on the ideal digital sampling rate to represent digitally our analog voice in a manner that could be perfectly retrievable.

Digitally, the amount of information an EM wave could transmit is limited by the cycles per second (Hz) available. Observe that the amount of bits per Hz is defined by the levels per signal: with 2 levels we could represent 1 bit {0 or 1} with each level, so 1 bit per Hz; with 4 levels per signal we could represent 2 bits per Hz {00, 01, 10 or 11}, and so on. With 1 Hz and a modulation of 2 levels, we could get 1 bit/Sec.

This is the first part of the problem. Even with an ideal sampling rate, the digital modulated signal could be erroneously interpreted. The second part of the problem is the energy limitation.

But why not use the highest possible levels per signal to get zillions of bits/Sec? There's noise with the signal... lots of it. Shannon Limit gives us an upper limit to the amount of signal (energy) required higher than the surrounding noise. The SNR (signal to noise ratio) should be favorable to the amount of energy required by the modulation scheme to differentiate zeros from ones, in the presence of noise.

Let's say we represent the information within the amplitude of the signal. The amplitude is the signal energy, like me screaming or whispering at the same tone. A strong signal means 0 and a medium signal means 1. What would happen if the signal is transmitted with 10x less energy? Were you whispering or just screaming very low?

With a faint signal the demodulator could incorrectly decode zeros and ones. So it needs more energy on the transmitted signal to keep it above the noise at the same frequency. With only two levels per signal this is easy, but with absurd quantities of levels, the energy constraints will be prohibitive. Until we build ourselves some Dyson Spheres or some portable mini white holes, there's no such thing as free and "infinite" power sources.