The K-Folds technique is easy to understand and quite popular. Compared to other Cross Validation approaches, it generally results in a less biased model. The key benefit of K-Folds is that it ensures that all observations from the original dataset have the chance to appear in both the training and test sets. This is particularly useful when dealing with limited input data.