It would not recognize those and that's exactly overfitting, learning ONLY it's dataset, but not the pattern within the dataset that is general and can be applied to new data.

If this happens does also depend on how complex your ML model is though (compared to the amount of input data). The simpler it is, the more resistant it is to overfitting (but also the less complex the pattern is allowed to be).

There is a scientist joke: "If you want to perfectly fit a linear regression just give it 2 datapoints". The linear regression is pretty much the simplest model, but giving it a too small dataset makes even that useless.