Cross-validation is an evaluation technique used to assess the performance of machine learning models on time series data. In time series analysis, special care needs to be taken due to the temporal nature of data. Methods like rolling window cross-validation or forward chaining can be employed to simulate real-world scenarios and provide robust performance estimation.