Adaptive sampling is a dynamic data collection strategy that adjusts the sampling process based on real-time analysis of the data being collected, optimizing resource allocation and improving the efficiency of data gathering. It is particularly useful in scenarios where the data landscape is heterogeneous or where certain areas of the data space are more informative than others.