The reason for this may be that the market is made up of interacting learning machines (if you subsume humans among them). Thus, every algorithm introduced changes the basis on whcih the algorithm was selected. Talk about moving targets...
I agree, and the word I would use is competing machines. Every time me (or my algo) bid up a security price I remove that "cheapness" signal from a competitor, increasing the noise they have to deal with and vice versa. ML hates noisy data. Returns are very noisy.
ML has a much easier time with data generated from situations that are lacking competition, such as data from any process inside a company, e.g. consumer behavior. These are problems that want to be solved.
