Model capacity refers to the ability of a machine learning model to fit a wide variety of functions, which is determined by the complexity and number of parameters within the model. A model with higher capacity can capture more intricate patterns in the data but is also more prone to overfitting if not properly regularized or if trained on insufficient data.