Linear Regression model visualization I am trying to visualize, how does the linear regression model draw a straight line when we have multiple features and one label to predict. Like when we have 1 feature and 1 label, we can easily plot them on a 2-D graph and draw a straight line. Even if we have two features and one label, we can still plot them on a 3-D graph but I couldn't able to visualize, what will happen when we have 20 features. Will algorithm use 20-D graph or am I missing something.

I am new to machine learning. So this question can come as naive.
If there are 20 independent variables and 1 dependent variable, a linear regression model can be viewed as a 20-dimensional hyperplane in 21-dimensional space. The hyperplane is not "vertical" with respect to any independent variable. So if you pick a value for each of the 20 independent variables and draw a vertical line at the point consisting of those values, it will cross the hyperplane once at the height that the model outputs when you plug in the values of the independent variables.