Step 1: Write out the system of equations.
The matrix equation \(Ax=b\) expands to the three scalar equations
\[
x_1+0x_2+2x_3=1
\]
\[
-x_1+x_2+0x_3=3
\]
\[
0x_1+x_2+2x_3=0
\]
Step 2: Check whether the coefficient matrix is singular.
Compute the determinant of \(A\) by expanding along the first row:
\[
\det(A)=1(1\times2-0\times1)-0(-1\times2-0\times0)+2(-1\times1-1\times0)
\]
\[
=1(2)-0(-2)+2(-1)=2-0-2=0
\]
Since \(\det(A)=0\), the matrix \(A\) is singular, so the system either has no solution or infinitely many; it cannot have exactly one unique solution. This already rules out option (B).
Step 3: Eliminate \(x_1\) using the first two equations.
From equation 1:
\[
x_1=1-2x_3
\]
Substitute into equation 2:
\[
-(1-2x_3)+x_2=3
\]
\[
-1+2x_3+x_2=3
\]
\[
x_2=4-2x_3
\]
Step 4: Substitute into the third equation and check consistency.
Equation 3 says
\[
x_2+2x_3=0
\]
Substituting \(x_2=4-2x_3\):
\[
(4-2x_3)+2x_3=0
\]
\[
4=0
\]
This is a false statement, independent of \(x_3\). No choice of \(x_1,x_2,x_3\) can make all three equations hold at once.
Step 5: Interpret the contradiction.
A singular coefficient matrix together with an inconsistent right-hand side (the rank of \(A\) is less than the rank of the augmented matrix \([A\,|\,b]\)) means the system is inconsistent, so it has no solution at all, not infinitely many.
Step 6: Rule out the remaining options.
(B) \(1\): Already ruled out, since \(\det(A)=0\) means a unique solution is impossible.
(C) \(6\): A linear system never has exactly \(6\) solutions; the solution count for a linear system is always \(0\), \(1\), or infinite. Incorrect.
(D) infinitely many: This would need the system to be consistent, but Step 4 showed the direct contradiction \(4=0\). Incorrect.
Final Answer:
The system \(Ax=b\) has
\[
\boxed{0 \text{ solutions}}
\]