Empty or missing data. Null is not equal to 0. For example: with a dataset that is a list of purchase events, there may be a field called "price." If this field is missing from some events, the value of price in those events is "null." In this example a price of 0 might mean "free," while a null might mean "unknown" or "N/A."
Scuba works well with data that has lots of null. It is common to use Scuba with datasets that have thousands of fields, most of which are null for many events. This often happens when data is loaded from many sources into the same table in Scuba. For example, a purchase event might have a price, while a photo upload event has a photo name, and a sensor reading has a color temperature in degrees C. These will all be null in the other kinds of events (purchase price probably doesn't record color data), but Scuba can handle the null values.