Handling feature drift in a Feature Store involves detecting changes in the statistical properties of the features and taking appropriate actions to mitigate the impact on the models. This can be achieved by monitoring the features for drift, using statistical tests to detect significant changes, and updating the features or retraining the models as needed. The strategies include implementing drift detection mechanisms, defining thresholds for drift, and automating the mitigation processes.