Overfitting happens when a machine learning model has become too attuned to the data on which it was trained and, therefore, loses its applicability to any other dataset. A model is overfitted when it is so specific to the original data that trying to apply it to data collected in the future would result in problematic or erroneous outcomes and less-than-optimal decisions.