Machine Learning, Overfitting.
In statistics, the goodness of fit refers to how closely a model’s predicted values match the observed (true) values. A model that has learned the noise instead of the signal is considered “overfit” because it fits the training dataset but has a poor fit with new datasets. This is a common problem