Let us have the training dataset consisting of $3$ data points $($with coordinates on the XoY plane in the form of $($x$,$y$))$: $(-2,0),(0,2),$ and $(2,0).$ Predict the Y value for the input with: X $=-1\mathrm{.}1$ for the $1-$NN Regression method with Manhattan $($or l$1)$ metric.

Note: input features are $1-$dimensional $($x$-$coordinate$),$ while output label is y$-$coordinate on the XoY plane.