Giving recommendations to new user based on model's current status.

Every tutorial I looked into gives recommendations based on users in the dataset. What if a new one appears? Lets say it is a case where user AA (model during training took data from users A->Z) made some searches/ratings (similarly we can build the Dataframe with user_id, movie_title, user_rating, etc).

If an unknown user is simply entered into the model then (obviously) the model won't be of much use. What I've been thinking is to take in the additional information and using whatever we have at the moment find the most similar user (typical CF) and make the initial query based off that one.

Is there any way to implement this? I'd like to pass the mini-dataframe (with the new user's ratings) as an input of sorts but I am not exactly certain how I should handle it afterwards. How can I add this additional information to my model?