It's not that the physics can't be modeled, but figuring out the appropriate models is probably harder than it looks. Every sensor and actuator has quirks. Does it matter how much your airframe flexes? Does the turbulence caused by some little protrusion matter enough to model? You aren't going to model every individual molecule, but how much detail is enough to be right?

The elegant thing about using machine learning is that you don't need to build any models at all. And you can develop the ML technique once and then reuse it to train different hardware configurations, instead of incurring the cost of modeling every one.