Your question is Handling Missing Values in ML. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You are training a supervised learning model and notice that several input features have missing values. You need a practical way to prepare the data without distorting the signal or introducing leakage.
How would you handle a dataset with missing values?