Soft continuum robots offer unique properties that cannot be achieved using rigid linkage-based robotic bodies. Their dexterity and intrinsic compliance deliver the ability to navigate constrained environments and operate in unprecedented ways. Although the Jacobian velocity matrix based method is a widely used approach to solve inverse kinematics (IK) problems for traditional rigid robots, its drawbacks emerge while solving IK problems of continuum robots, such as high computational cost with no solution guarantees. Attempts to provide alternative solutions must overcome the computational complexity and vast functional workspace of continuum manipulator postures. Here, we propose a heuristic approach, the State Lattice based Inverse Kinematics Solver (SLInKi), which uses concepts originally developed for solving path-finding problems to solve the IK problem of a soft continuum robot. This algorithm is intuitive, runs in real time, and combines the strengths of two algorithms in a unique package that surpasses existing methods in adjustability and efficiency. Several simulation case studies and real robot experiments demonstrate that the proposed approach is flexible, computationally efficient, and highly accurate compared to the state of the art.