The correct answer is D. multiple linear regression.
Binary classification is a supervised machine learning task that involves predicting whether an instance belongs to one of two classes. Multilabel classification is a supervised machine learning task that involves predicting which of several classes an instance belongs to. Simple linear regression is a supervised machine learning task that involves predicting a continuous value based on a single predictor variable. Multiple linear regression is a supervised machine learning task that involves predicting a continuous value based on multiple predictor variables.
In the case of predicting the selling price of a house, the number of bedrooms, number of kitchens, number of bathrooms, the year the house was built, and the square footage of the lot are all predictor variables. The selling price of the house is the target variable. Multiple linear regression is the appropriate task to use because there are multiple predictor variables and the target variable is continuous.
Binary classification would be inappropriate because the selling price of a house is a continuous value, not a binary value. Multilabel classification would be inappropriate because there is only one target variable, not multiple target variables. Simple linear regression would be inappropriate because there are multiple predictor variables.