Frequency masking is a data augmentation technique used in audio processing to improve the robustness of machine learning models by randomly masking certain frequency bands in the input spectrogram. This method helps models to generalize better by preventing overfitting to specific frequency patterns and encouraging the learning of more diverse audio features.