Bayes rule is one of the building blocks of probability theory. It stems from conditional probability and joint probability and extends beyond.
We will explain this in a simple way by again taking an example from cricket. In cricket, pitch condition varies as you go from one place to another and it is one of the factors that can be significant when deciding the team. The outcome can also be dependent upon it.
Let's say the Indian team goes to Australia for a game and we have to predict the belief of an Indian player scoring a century (100 runs) in the game. If that player has got experience of playing in that country, we might say with strong belief that he might score a century. But, there is another player who is a first-timer in this country. What would the the prior belief be for him? Of course, many would have less belief that he would score a century.
However, our prior belief will change as we see the way the player is performing. That is, more data about the player will be...