This is very false. Least squares regression fitting, Chebychev polynomial approximation, and maximum likelihhod estimators all existed at the time and those are all classic examples of standard machine learning. The term “machine learning” essentially encompasses any type of algorithm that expresses inductive statistical reasoning. Even just elementary school descriptive statistics is machine learning. “Machine learning” is a super old subfield of applied mathematics. The fact that the terminology “machine learning” didn’t exist until things like perceptron and SVMs came along is utterly irrelevant semantic hairsplitting.

But ML is essentially just function approximation, and that definitely existed back then.

I know this is super pedantic, but it's important to remember the roots of things, and that even things which appear new have precursors that are much older than a lot of people realise.