The Bayesian Information Criterion (BIC) is a statistical tool used to select among a set of models, penalizing models with more parameters to avoid overfitting. It is based on the likelihood function and provides a balance between model fit and complexity, favoring simpler models when they fit the data nearly as well as more complex ones.