How likely are we to make the observations of data if the parameters of our model θ are correct.
When you have your model, it is usually straightforward to calculate this likelihood. For a simple example, if we are modelling coin tosses as a fair coin being tossed, and we see two heads in a row, is given by:
Picking a good model that you can parameterise is a key part of this process. Ben Lambert's book gives you this framework for picking a good model: