Is ML all about statistical regressions at its core?

For the past several months I've been interested in some Machine Learning and I can't help but notice that nomatter what kind of learning algorithm I'm using - at its core lies a simple polynomial or logistic regression. Today I went back to the most basic definition that I could find:

"Machine learning, a branch of artificial intelligence, concerns the construction and study of systems that can learn from data."

The fact that we're creating mathematical hypotheses based on data ALWAYS means that you're doing some kind of statistical regression ?

If I'm wrong, can you please provide an example where this doesn't hold true.