For any numerical feature F and any given point (X, Y) of the plot, Y is equal to the difference between:
* the average of the prediction on (a sample of) the test set;
* and the average prediction of the same data where, for all rows, the feature F is set to X.
I'm not sure I understand what you mean by "target" in this context. Partial dependence can not be computed for the model target but only for model input features.
Hope this helps.