Decision Boundary - What is the utility

What does the decision boundary represent?
The course shows up in a graph 2 features one on the x-axis and the other one on the y-axis. I cannot understand the relationship between them, because they are different features (centimeters vs ages).
Actually, the sigmoid function and the threshold you define determine if the result represents A or B, for instance, if a tumor is malignant or benign.

What am I missing?

Thanks.

It’s a 3D plot. The horizontal and vertical axes are the two features. The symbols represent the classifications, where ‘o’ represents a prediction of 0.0 (or False) and ‘s’ represents 1.0 (or True).

The decision boundary is where the predicted value is exactly 0.5 - halfway between True and False.

Thanks