Understanding On-policy First Visit Monte Carlo Control algorithm

Question

I am going through the Monte Carlo methods, and it's going fine until now. However, I am actually studying the On-Policy First Visit Monte Carlo control for epsilon soft policies, which allows us to estimate the optimal policy in Reinforcement Learning.

I am having troubles understanding the step in blue of the algorithm. Is the pair St, At NEVER supposed to appears in the given set of states ? In this case, the following pseudo-code will never get realized ? What is the specific case where St, At appears in the set of Action-States ?

Please feel free to ask more details if my question isn't clear enough.

The algorithm is taken from the reinforcement learning book written by R.Sutton and A. Barto.