The principle of statistics is simple enough: take real data from a sample and construct one model that works in various scenarios. However, issues with overfitting arise when the chosen model has a wide range of freedom and can remember the uniqueness of each observation without understanding the underlying phenomenon. Thus the model sends back rules that do not apply, and becomes extremely sensitive to the slightest variation.
For example, an overfitted model that takes age into account might give two very different results for two individuals born just a few days apart.
