LIME works by creating a new dataset consisting of perturbations of the original data and the corresponding model predictions. It then fits a simple, interpretable model (like a linear model) to this new dataset. This simple model is used to approximate the decision boundary of the complex model in the local region around the instance being explained. By examining the coefficients of the simple model, one can understand which features are most important for the prediction.
