Basically situations where you have a few data sources for the same thing, all with their own margins of error, update rate, etc. And you want to combine them to get one better data point. Eg in robotics, you can put together GPS, vision (e.g. from visual markers or perceived movement) and wheel encoder (how many times did the wheel spin, where do I think I am based on that) data to get one much more accurate location point.