Out-of-Distribution

Think of it like a GPS navigation system that's only been trained on city roads, but then you take it off-roading. It's when a model encounters data that's significantly different from what it was trained on, making it harder for the model to make accurate predictions. This can happen when the real-world data has changed or when the model is applied to a new domain or task.