When I have encountered for the first time ML term I decided to learn what is that new great stuff. To my great surprise this was a typical old new thing called "statistical inference" in the days when I was working as a statistician.

There were a few new things, like ignoring model, choosing right variables, whatever was available was thrown into the equation, if it was clear that such "model" is over-fitted, there were some methods to overcome this by adding some random coefficients to the model that were smoothing it a little.

So, the naming is there... could be modified by adding some clarification that we don't care that much about understanding model we plan to use.