Clarify the role of pivoting in QR factorization (#29976)

* Clarify the role of pivoting in QR factorization

Ref: https://discourse.julialang.org/t/left-matrix-division-with-singular-matrix/15503

* Update qr.jl

(cherry picked from commit e5e6b64)

stdlib/LinearAlgebra/src/qr.jl

@@ -318,7 +318,9 @@ Iterating the decomposition produces the components `Q`, `R`, and if extant `p`.
 
 The following functions are available for the `QR` objects: [`inv`](@ref), [`size`](@ref),
 and [`\\`](@ref). When `A` is rectangular, `\\` will return a least squares
-solution and if the solution is not unique, the one with smallest norm is returned.
+solution and if the solution is not unique, the one with smallest norm is returned. When
+`A` is not full rank, factorization with (column) pivoting is required to obtain a minimum
+norm solution.
 
 Multiplication with respect to either full/square or non-full/square `Q` is allowed, i.e. both `F.Q*F.R`
 and `F.Q*A` are supported. A `Q` matrix can be converted into a regular matrix with