Cross validation is a statistical method used to estimate the performance and reliability of different predictive models. It is especially important in the context of business because it helps ensure that the models used for decision-making and forecasting are accurate and generalizable to new data sets. By partitioning the data into multiple subsets and testing the model on each part, businesses can avoid overfitting and select the best model for their needs.