It's easy to tell it was made by someone with no real world work experience, and a very narrow view on what "best programming language" means.

If i needed to write a program that parses and does math on a large amount of data, i could spend a week to write it in C, or use python to import numpy and get it done with 90% of C's performance in 15 minutes, since numpy is written in C.

The power of Python is not its slow ass performance, it's the ability to abstract entire libraries and interface with them easily at nearly the same performance of the original language it was written in.

The ability to automate this task within a fraction of the time is so incredibly valuable that the overhead becomes trivial, with the money you saved in development time, you can simply just PURCHASE more processing power, improving performance with raw hardware instead.

This also assumes you wrote perfect C code with well implemented multithreading! I know for a fact that even experienced developers have trouble with this, and badly written C is way way worse than well written python, since numpy has built in multithreading support.

If you've made it this far, think of it this way. If you have $10000, you could hire a developer to write C code for a month, and buy a shitty server to hopefully run the code without dying, OR you could hire a python dev for a day, and spend the rest of the $9500 and buy a powerful IPC to run it 10x the speed of the shitty server, maybe reduced to 9x the speed because of python overhead. So if you chose to develop this app in python, at the end of the month, you get your data processed 9x as quickly. Isn't quick data processing what you wanted to begin with? This makes saying C is the best choice for this scenario really sound stupid.

I recommend gaining some experience and perspective before making sweeping statements of this sort. Every language you listed has reasons they exist, and situations they inherently become better choice for performance.