The Actual by Predicted plot shows the actual Y values on the Y axis and the jackknife predicted values on the X axis. One measure of goodness-of-fit is how well the points lie along the diagonal (Y = X) of the plot.
The jackknife values are not true jackknife values in that the model is not re-fit with the associated row for each Y excluded. Rather, the row is excluded from the prediction model for each associated Y but the correlation parameters retain the contribution of the row in them. For Gaussian processes that perfectly interpolate the data this jackknife procedure provides predictions that are not equal to the input.