That's a very accurate way of saying what an ML model really stands for!

We let the neural network discover the pattern, by trying to minimize a defined loss function. So the only information we manually communicate is the conditions on which the model must declare itself "correct" (which is the loss function). Along with the base assumption, which is usually the math used to construct the neural network .